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tiny_CaLL_r1_O1_f1_LT_checkpoint-511
MSey/tiny_CaLL_r1_O1_f1_LT_checkpoint-511
tiny_CaLL_r1_O1_f1_LT_checkpoint-511 is a text generation model from MSey. Use it when you need the model to write or continue text. It is set up for transformers.
We fine-tuned our base model for 21 epochs on the Ca dataset, epoch 1 showed the best macro average f1 score on the evaluation dataset.
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.safetensors4.4 GB · 100%
At a glance
- Task
- Text Generation
- Library
- transformers
- Model type
- llama
- Access
- Public
- Created
- Sep 11, 2024
- Updated
- Sep 17, 2024
- SHA
- d148cec0
Base models
Model card
From the Hugging Face model README
Model Card for Model ID
We fine-tuned our base model for 21 epochs on the Ca dataset, epoch 1 showed the best macro average f1 score on the evaluation dataset.
Context format
"### Context\n\nText to analyse.\n\n###Answer"
Metric
eval_AVGf1 0.9102075019834961
eval_DIAGNOSIS.f1 0.8808602150537634
eval_DIAGNOSIS.precision 0.8943231441048035
eval_DIAGNOSIS.recall 0.8677966101694915
eval_DIAGNOSTIC.f1 0.9472166137871358
eval_DIAGNOSTIC.precision 0.9624853458382181
eval_DIAGNOSTIC.recall 0.9324247586598523
eval_DRUG.f1 0.9440145653163405
eval_DRUG.precision 0.9792256846081209
eval_DRUG.recall 0.9112478031634447
eval_MEDICAL_FINDING.f1 0.9092427259297321
eval_MEDICAL_FINDING.precision 0.9073195744135367
eval_MEDICAL_FINDING.recall 0.9111740473738414
eval_THERAPY.f1 0.8697033898305084
eval_THERAPY.precision 0.8729399255715046
eval_THERAPY.recall 0.8664907651715039
eval_accuracy 0.9618960382191458
eval_f1 0.7632318301785055
eval_loss 0.006697072647511959
eval_model_preparation_time 0
eval_precision 0.6619246861924686
eval_recall 0.9011526605012733
eval_runtime 341.5967
eval_samples_per_second 23.952
eval_steps_per_second 5.99
test_AVGf1 0.8676664044743045
test_DIAGNOSIS.f1 0.7754658946987515
test_DIAGNOSIS.precision 0.7846942511900403
test_DIAGNOSIS.recall 0.7664520743919886
test_DIAGNOSTIC.f1 0.9211950129381322
test_DIAGNOSTIC.precision 0.9346062052505967
test_DIAGNOSTIC.recall 0.9081632653061225
test_DRUG.f1 0.9448028673835126
test_DRUG.precision 0.9835820895522388
test_DRUG.recall 0.9089655172413793
test_MEDICAL_FINDING.f1 0.879590997238056
test_MEDICAL_FINDING.precision 0.8656025907934305
test_MEDICAL_FINDING.recall 0.8940389439732409
test_THERAPY.f1 0.8172772501130711
test_THERAPY.precision 0.8187584956955143
test_THERAPY.recall 0.8158013544018059
test_accuracy 0.9665184459433998
test_f1 0.7391588362393848
test_loss 0.009836438111960888
test_model_preparation_time 0
test_precision 0.6447795213465416
test_recall 0.865905344949376
test_runtime 394.9961
test_samples_per_second 24.023
test_steps_per_second 6.008
- Task
- Text Generation
- Library
- transformers
- Type
- llama
- Languages
- de
- Created
- Sep 11, 2024
- Updated
- Sep 17, 2024